Perfusion imaging can be used to detect both physical structure within the body and tissue function and viability. It is particularly useful for studying patients with brain, heart or liver damage, e.g. as a result of stroke, tumours, infarct, etc. Examples of perfusion imaging techniques include Magnetic Resonance Imaging (MRI), Medical ultrasonography (sonography), Positron emission tomography (PET) and Computed Tomography (CT).
In general MRI perfusion techniques, a bolus of a contrast agent (e.g. a gadolinium chelate such as those marketed as Omniscan® or Magnevist® by Amersham and Schering) is administered into the patient's vascular system and images from the region of interest are collected for a period covering the transit of the contrast agent bolus through the tissue in the region of interest. For example, in MRI, fast image acquisition sequences, e.g. spin echo; gradient recall (GRASS or FLASH), echo planar (EPI), RARE, hybrid, half excitation, etc. are used. Such sequences and bolus administration of MR contrast agents for perfusion imaging are well known in the art (see for example “Biomedical Magnetic Resonance Imaging”, Ed. Wehrli et al, VCH, 1988).
In clinical practice, it is common for the perfusion image series to be inspected and the results to be assessed qualitatively.
However in many instances a quantified result, e.g. an absolute measurement of regional blood flow, regional blood volume, regional mean transit time, regional time of arrival, regional permeability surface product and regional time to peak are desired (see for example Rempp et al, Radiology 193: 637-641 (1994) and Vonken et al, MRM 41: 343-350 (1999)).
Pharmacokinetic modelling is used to extract voxel specific values for blood plasma flow, blood plasma volume, mean transit time, extravascular extracellular volume, permeability surface area product and time to peak or less physiological perfusion parameters such as the capillary transfer constant, Ktrans. Recirculation of contrast and contrast leakage is included.
The most general pharmacokinetic model introduced so far for MR multi-pass perfusion imaging is the adiabatic approximation model of Johnson and Wilson (aaJW) [Henderson et al. JMRI, Vol. 12: 991-1003 (2000)]. However, the presence of multiple parameters in the aaJW model has made it relatively unstable and highly sensitive to poor signal-to-noise ratio in the underlying data.
The observed tracer perfusion signal of each voxel is a convolution of an unknown voxel specific arterial input function and of an unknown voxel specific tissue residue function (or impulse response function).
The tissue residue function describes the fraction of contrast agent still present in a tissue region at time t and is thus a function dependent on the physiological parameters of the tissue, e.g. blood volume and mean transit time. The arterial input function describes how the contrast agent is delivered to the tissue voxel, and as such gives an impression of the vascular structure in the organ.
With pharmacokinetic modelling, the unknown voxel specific tissue residue function is assumed to have a known parametric form, but with unknown parameter values. The time delay of the tracer arrival and the time to peak of the tracer are specified by the voxel specific arterial input function factor alone. All the remaining perfusion parameters are specified by the flow scaled voxel specific tissue residue function factor.
All known methods using multi-pass pharmacokinetic modelling to find perfusion parameters have problems. For example, the unknown voxel specific arterial input functions may be replaced by a single known arterial input function. This value is generally found by manual or automated identification of voxels inside a vessel. This vessel may be remote from the tissue of interest. Besides, all delay and dispersion of the arterial input function from the vessel used to the tissue of interest are ignored. These modelling simplifications may induce large errors in the estimated perfusion parameters. Ideally, voxel specific arterial input functions should be used to avoid delay and dispersion. In addition, high flow speeds, movements and saturation induce large variability in the arterial input function of major vessels when measured in serial examinations of the same patient.